A dual controllability analysis of influenza virus-host protein-protein interaction networks for antiviral drug target discovery

Ackerman, Emily E.; Alcorn, John F.; Hase, Takeshi; Shoemaker, Jason E.

In total, this two-part network controllability analysis for a host protein-protein interaction network (HIN) and an integrated influenza virus-host protein-protein interaction network (VIN) aims to enhance the prediction of antiviral drug targets for influenza A virus. While robust controllability methods have previously been applied to study PPI networks [29] , past analysis focuses only on the classification of virus interacting proteins and does not evaluate before and after the addition of virus-host interactions to the network. A global controllability analysis has never been applied to PPI networks. The unique construction of the VIN includes experimentallyderived virus-host interaction data [41] which represents opportunities for the virus to manipulate host intracellular machinery using protein-protein interactions. Here, analysis of the transition between the healthy and infected network states and further investigation of virus interacting and driver proteins has identified 24 proteins as regulatory markers of the infected state. This protein set is noted for its characteristics in topology, controllability, and functional roles within the infected cell: results that are summarized in Table 5 . Our workflow observes both the effect of structural changes to the network in the case of potential protein knock outs, as well as each protein's role in all MISs, representing all possible ways of controlling the system. In combination, network approach and results provide deeper understanding of how changes to cell behavior at the onset of infection are able to occur through the work of a small set of viral proteins. Through understanding the system in this way, we present the possibility to "outsmart" viral attack by dismantling the control structure which allows the viral infection to take hold.